StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants.

Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base pairs) of uncertain significance are the genetic cause of a portion of these unresolved cases. As sequencing methods using long or linked reads become more accessible and SV detection algorithms improve, clinicians and researchers are gaining access to thousands of reliable SVs of unknown disease relevance. Methods to predict the pathogenicity of these SVs are required to realize the full diagnostic potential of long-read sequencing. To address this emerging need, we developed StrVCTVRE to distinguish pathogenic SVs from benign SVs that overlap exons. In a random forest classifier, we integrated features that capture gene importance, coding region, conservation, expression, and exon structure. We found that features such as expression and conservation are important but are absent from SV classification guidelines. We leveraged multiple resources to construct a size-matched training set of rare, putatively benign and pathogenic SVs. StrVCTVRE performs accurately across a wide SV size range on independent test sets, which will allow clinicians and researchers to eliminate about half of SVs from consideration while retaining a 90% sensitivity. We anticipate clinicians and researchers will use StrVCTVRE to prioritize SVs in probands where no SV is immediately compelling, empowering deeper investigation into novel SVs to resolve cases and understand new mechanisms of disease. StrVCTVRE runs rapidly and is publicly available.

SAM-DTA: a sequence-agnostic model for drug-target binding affinity prediction.

Drug-target binding affinity prediction is a fundamental task for drug discovery and has been studied for decades. Most methods follow the canonical paradigm that processes the inputs of the protein (target) and the ligand (drug) separately and then combines them together. In this study we demonstrate, surprisingly, that a model is able to achieve even superior performance without access to any protein-sequence-related information. Instead, a protein is characterized completely by the ligands that it interacts. Specifically, we treat different proteins separately, which are jointly trained in a multi-head manner, so as to learn a robust and universal representation of ligands that is generalizable across proteins. Empirical evidences show that the novel paradigm outperforms its competitive sequence-based counterpart, with the Mean Squared Error (MSE) of 0.4261 versus 0.7612 and the R-Square of 0.7984 versus 0.6570 compared with DeepAffinity. We also investigate the transfer learning scenario where unseen proteins are encountered after the initial training, and the cross-dataset evaluation for prospective studies. The results reveals the robustness of the proposed model in generalizing to unseen proteins as well as in predicting future data. Source codes and data are available at https://github.com/huzqatpku/SAM-DTA.

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.

BACKGROUND: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb). RESULTS: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods. CONCLUSIONS: VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Hidden Charge Order and Multiple Electronic Instabilities in EuTe4.

The rare-earth telluride compound EuTe4 exhibits a charge density wave (CDW) and an unconventional thermal hysteresis transition. Herein, we report a comprehensive study of the CDW states in EuTe4 by using low-temperature scanning tunneling microscopy. Two types of charge orders are observed at 4 K, including a newly discovered spindle-shaped pattern and a typical stripe-like pattern. As an exotic charge order, the spindle-shaped CDW is off-axis and barely visible at 77 K, indicating that it is a hidden order developed at low temperature. Based on our first-principles calculations, we reveal the origins of the observed electronic instabilities. The spindle-shaped charge order stems from a subsequent transition based on the stripe-like CDW phase. Our work demonstrates that the competition and cooperation between multiple charge orders can generate exotic quantum phases.

DNMT1/DNMT3a-mediated promoter hypermethylation and transcription activation of ICAM5 augments thyroid carcinoma progression.

Promoter methylation is one of the most studied epigenetic modifications and it is highly relevant to the onset and progression of thyroid carcinoma (THCA). This study investigates the promoter methylation and expression pattern of intercellular adhesion molecule 5 (ICAM5) in THCA. CpG islands with aberrant methylation pattern in THCA, and the expression profiles of the corresponding genes in THCA, were analyzed using bioinformatics. ICAM5 was suggested to have a hypermethylation status, and it was highly expressed in THCA tissues and cells. Its overexpression promoted proliferation, mobility, and tumorigenic activity of THCA cells. As for the downstream signaling, ICAM5 was found to activate the MAPK/ERK and MAPK/JNK signaling pathways. Either inhibition of ERK or JNK blocked the oncogenic effects of ICAM5. DNA methyltransferases 1 (DNMT1) and DNMT3a were found to induce promoter hypermethylation of ICAM5 in THCA cells. Knockdown of DNMT1 or DNMT3a decreased the ICAM5 expression and suppressed malignant properties of THCA cells in vitro and in vivo, which were, however, restored by further artificial ICAM5 overexpression. Collectively, this study reveals that DNMT1 and DNMT3a mediates promoter hypermethylation and transcription activation of ICAM5 in THCA, which promotes malignant progression of THCA through the MAPK signaling pathway.

Assessing predictions on fitness effects of missense variants in HMBS in CAGI6.

This paper presents an evaluation of predictions submitted for the "HMBS" challenge, a component of the sixth round of the Critical Assessment of Genome Interpretation held in 2021. The challenge required participants to predict the effects of missense variants of the human HMBS gene on yeast growth. The HMBS enzyme, critical for the biosynthesis of heme in eukaryotic cells, is highly conserved among eukaryotes. Despite the application of a variety of algorithms and methods, the performance of predictors was relatively similar, with Kendall's tau correlation coefficients between predictions and experimental scores around 0.3 for a majority of submissions. Notably, the median correlation (≥ 0.34) observed among these predictors, especially the top predictions from different groups, was greater than the correlation observed between their predictions and the actual experimental results. Most predictors were moderately successful in distinguishing between deleterious and benign variants, as evidenced by an area under the receiver operating characteristic (ROC) curve (AUC) of approximately 0.7 respectively. Compared with the recent two rounds of CAGI competitions, we noticed more predictors outperformed the baseline predictor, which is solely based on the amino acid frequencies. Nevertheless, the overall accuracy of predictions is still far short of positive control, which is derived from experimental scores, indicating the necessity for considerable improvements in the field. The most inaccurately predicted variants in this round were associated with the insertion loop, which is absent in many orthologs, suggesting the predictors still heavily rely on the information from multiple sequence alignment.

Predicting the impact of rare variants on RNA splicing in CAGI6.

Variants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant's impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.

Reciprocal adaptation of rice and Xanthomonas oryzae pv. oryzae: cross-species 2D GWAS reveals the underlying genetics.

A 1D/2D genome-wide association study strategy was adopted to investigate the genetic systems underlying the reciprocal adaptation of rice (Oryza sativa) and its bacterial pathogen, Xanthomonas oryzae pv. oryzae (Xoo) using the whole-genome sequencing and large-scale phenotyping data of 701 rice accessions and 23 diverse Xoo strains. Forty-seven Xoo virulence-related genes and 318 rice quantitative resistance genes (QR-genes) mainly located in 41 genomic regions, and genome-wide interactions between the detected virulence-related genes and QR genes were identified, including well-known resistance genes/virulence genes plus many previously uncharacterized ones. The relationship between rice and Xoo was characterized by strong differentiation among Xoo races corresponding to the subspecific differentiation of rice, by strong shifts toward increased resistance/virulence of rice/Xoo populations and by rich genetic diversity at the detected rice QR-genes and Xoo virulence genes, and by genome-wide interactions between many rice QR-genes and Xoo virulence genes in a multiple-to-multiple manner, presumably resulting either from direct protein-protein interactions or from genetic epistasis. The observed complex genetic interaction system between rice and Xoo likely exists in other crop-pathogen systems that would maintain high levels of diversity at their QR-loci/virulence-loci, resulting in dynamic coevolutionary consequences during their reciprocal adaptation.

A fluorescent probe based on cyclochalcone for detecting peroxynitrite.

A novel cyclic chalcone fluorescent probe C-PN was synthesized to detect ONOO-. After reaction with peroxynitrite, the double bond of C-PN in the cyclic chalcone structure was disconnected, which caused the change of intramolecular charge transfer (ICT) effect, emitting blue fluorescence and quenching orange red fluorescence. Visible to the naked eye, the color of the probe solution changed. The probe showed low sensitivity (detection limit = 20.2 nm), short response time (less than 60 s) at low concentration of ONOO-, good visibility, and good selectivity and stability for ONOO-.

FBXO38 mediates PD-1 ubiquitination and regulates anti-tumour immunity of T cells.

Dysfunctional T cells in the tumour microenvironment have abnormally high expression of PD-1 and antibody inhibitors against PD-1 or its ligand (PD-L1) have become commonly used drugs to treat various types of cancer1-4. The clinical success of these inhibitors highlights the need to study the mechanisms by which PD-1 is regulated. Here we report a mechanism of PD-1 degradation and the importance of this mechanism in anti-tumour immunity in preclinical models. We show that surface PD-1 undergoes internalization, subsequent ubiquitination and proteasome degradation in activated T cells. FBXO38 is an E3 ligase of PD-1 that mediates Lys48-linked poly-ubiquitination and subsequent proteasome degradation. Conditional knockout of Fbxo38 in T cells did not affect T cell receptor and CD28 signalling, but led to faster tumour progression in mice owing to higher levels of PD-1 in tumour-infiltrating T cells. Anti-PD-1 therapy normalized the effect of FBXO38 deficiency on tumour growth in mice, which suggests that PD-1 is the primary target of FBXO38 in T cells. In human tumour tissues and a mouse cancer model, transcriptional levels of FBXO38 and Fbxo38, respectively, were downregulated in tumour-infiltrating T cells. However, IL-2 therapy rescued Fbxo38 transcription and therefore downregulated PD-1 levels in PD-1+ T cells in mice. These data indicate that FBXO38 regulates PD-1 expression and highlight an alternative method to block the PD-1 pathway.

Genomic variation in 3,010 diverse accessions of Asian cultivated rice.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

Dental pulp mesenchymal stem cell-derived exosomes inhibit neuroinflammation and microglial pyroptosis in subarachnoid hemorrhage via the miRNA-197-3p/FOXO3 axis.

BACKGROUND: Subarachnoid hemorrhage (SAH) is a severe stroke subtype that lacks effective treatment. Exosomes derived from human dental pulp stem cells (DPSCs) are a promising acellular therapeutic strategy for neurological diseases. However, the therapeutic effects of DPSC-derived exosomes (DPSC-Exos) on SAH remain unknown. In this study, we investigated the therapeutic effects and mechanisms of action of DPSC-Exos in SAH. MATERIALS AND METHODS: SAH was established using 120 male Sprague-Dawley rats. One hour after SAH induction, DPSC-Exos were administered via tail vein injection. To investigate the effect of DPSC-Exos, SAH grading, short-term and long-term neurobehavioral assessments, brain water content, western blot (WB), immunofluorescence staining, Nissl staining, and HE staining were performed. The role of miR-197-3p/FOXO3 in regulating pyroptosis was demonstrated through miRNA sequencing, bioinformatics analysis, and rescue experiments. The SAH model in vitro was established by stimulating BV2 cells with hemoglobin (Hb) and the underlying mechanism of DPSC-Exos was investigated through WB and Hoechst/PI staining. RESULTS: The expressions of pro-inflammatory cytokines (IL-1ß, IL-6, and TNF-α) were increased after SAH. DPSC-Exos alleviated brain edema and neuroinflammation by inhibiting the expression of FOXO3 and reducing NLRP3 inflammasome activation, leading to improved neurobehavioral functions at 24 h after SAH. In vitro, the expression of the NLRP3 inflammasome components (NLRP3 and caspase1-p20), GSDMD-N, and IL-18 was inhibited in BV2 cells pretreated with DPSC-Exos. Importantly, DPSC-Exos overexpressing miR-197-3p had a more obvious protective effect than those from NC-transfected DPSCs, while those from DPSCs transfected with the miR-197-3p inhibitor had a weaker protective effect. Functional studies indicated that miR-197-3p bound to the 3'-untranslated region of FOXO3, inhibiting its transcription. Furthermore, the overexpression of FOXO3 reversed the protective effects of miR-197-3p. CONCLUSIONS: DPSC-Exos inhibited activation of the NLRP3 inflammasome and related cytokine release via the miR-197-3p/FOXO3 pathway, alleviated neuroinflammation, and inhibited microglial pyroptosis. These findings suggest that using DPSC-Exos is a promising therapeutic strategy for SAH.

Osteopontin: A Novel Therapeutic Target for Respiratory Diseases.

Osteopontin (OPN) is a multifunctional phosphorylated protein that is involved in physiological and pathological events. Emerging evidence suggests that OPN also plays a critical role in the pathogenesis of respiratory diseases. OPN can be produced and secreted by various cell types in lungs and overexpression of OPN has been found in acute lung injury/acute respiratory distress syndrome (ALI/ARDS), pulmonary hypertension (PH), pulmonary fibrosis diseases, lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), and asthma. OPN exerts diverse effects on the inflammatory response, immune cell activation, fibrosis and tissue remodeling, and tumorigenesis of these respiratory diseases, and genetic and pharmacological moudulation of OPN exerts therapeutic effects in the treatment of respiratory diseases. In this review, we summarize the recent evidence of multifaceted roles and underlying mechanisms of OPN in these respiratory diseases, and targeting OPN appears to be a potential therapeutic intervention for these diseases.

Emerging Roles of Galectin-3 in Pulmonary Diseases.

Galectin-3 is a multifunctional protein that is involved in various physiological and pathological events. Emerging evidence suggests that galectin-3 also plays a critical role in the pathogenesis of pulmonary diseases. Galectin-3 can be produced and secreted by various cell types in the lungs, and the overexpression of galectin-3 has been found in acute lung injury/acute respiratory distress syndrome (ALI/ARDS), pulmonary hypertension (PH), pulmonary fibrosis diseases, lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), and asthma. Galectin-3 exerts diverse effects on the inflammatory response, immune cell activation, fibrosis and tissue remodeling, and tumorigenesis in these pulmonary disorders, and genetic and pharmacologic modulation of galectin-3 has therapeutic effects on the treatment of pulmonary illnesses. In this review, we summarize the structure and function of galectin-3 and the underlying mechanisms of galectin-3 in pulmonary disease pathologies; we also discuss preclinical and clinical evidence regarding the therapeutic potential of galectin-3 inhibitors in these pulmonary disorders. Additionally, targeting galectin-3 may be a very promising therapeutic approach for the treatment of pulmonary diseases.

Effects of Protection Time on Infection of Rice Panicle Blast.

Panicle blast, caused by Magnaporthe oryzae, is a destructive disease of rice worldwide. Clarifying the susceptibility of rice panicles at different stages is of great significance for effective disease management. Field experiments were conducted in two paddy fields at Wuyuan County in 2016 and 2017 to determine the effects of head covering and its timing on the infection of rice panicle blast. Results revealed that panicle blast was reduced significantly by covering rice heads with sulfuric acid paper bags, regardless of the covering time, ranging from initial heading to 15 days afterward, suggesting that rice panicles could be infected by blast pathogen even 15 days after initial heading. Panicle blast incidence was also found to be significantly influenced by plant dates, with higher panicle blast incidence observed in plots planted on early dates, suggesting adjusting plant dates could help rice panicles escape the infection by blast pathogen. The results from this study also highlighted the importance of cultivars and environmental conditions to panicle blast. In conclusion, besides planting blast-resistant cultivars, it is important to protect rice heads from the initial heading to the early dough stages, and fungicides should be applied according to infection warnings based on host, inoculum, and weather conditions.

One-Step Green Synthesis of Isoeugenol Methyl Ether from Eugenol by Dimethyl Carbonate and Phase-Transfer Catalysts.

In this paper, the green synthesis of isoeugenol methyl ether (IEME) from eugenol by O-methylation and isomerization is completed using a one-step green process. In the methylation reaction, dimethyl carbonate (DMC) was used as a green chemistry reagent instead of the traditional harmful methylation reagents, in accordance with the current concept of green chemistry. The phase transfer catalyst (PTC) polyethylene glycol 800 (PEG-800) was introduced into the isomerization reaction to break the barrier of difficult contact between solid and liquid phases and drastically reduce the reaction conditions by shortening the reaction time and reducing the alkalinity of the reaction system. The catalytic systems for the one-step green synthesis of IEME were screened, and it was shown that the catalytic system "K2CO3 + PEG-800" was the most effective. The effects of reaction temperature, n(DMC):n(eugenol) ratio, n(PEG-800):n(eugenol) ratio, and n(K2CO3):n(eugenol) ratio on eugenol conversion, IEME yield, and IEME selectivity were investigated. The results showed that the best reaction was achieved at a reaction temperature of 140 °C, a reaction time of 3 h, a DMC drip rate of 0.09 mL/min, and n(eugenol):n(DMC):n(K2CO3):n(PEG-800) = 1:3:0.09:0.08. As a result of the conversion of 93.1% of eugenol to IEME, a yield of 86.1% IEME as well as 91.6% IEME selectivity were obtained.

An experimental study of a novel external fixator based on universal joints for the rapid initial stabilization of mandibular comminuted fractures.

PURPOSE: Shaping and assembling contemporary external fixators rapidly for the severe mandibular fractures remains a challenge, especially in emergency circumstance. We designed a novel external fixator that incorporates universal joints to provide the stabilization for mandibular comminuted fractures. This study aims to confirm the efficacy of this novel external fixator through biomechanical tests in vitro and animal experiments. METHODS: In vitro biomechanical tests were conducted using 6 fresh canine with mandibular defect to simulate critical comminuted fractures. Three mandibles were stabilized by the novel external fixator and other mandibles were fixed by 2.5 mm reconstruction plates. All fixed mandibles were subjected to loads of 350 N on the anterior regions of teeth and 550 N on the first molar of the unaffected side. The stability was evaluated based on the maximum displacement and the slope of the load-displacement curve. In animal experiments, 9 beagles with comminuted mandibular fractures were divided into 3 groups, which were treated with the novel external fixation, reconstruction plate, and dental arch bar, respectively. The general observation, the changes in animals' weight, and the surgical duration were recorded and compared among 3 groups. The CT scans were performed at various intervals of 0 day (immediately after the surgery), 3 days, 7 days, 14 days, 21 days, and 28 days to analyze the displacement of feature points on the canine mandible and situation of fracture healing at 28 days. The statistical significance was assessed by the two-way analysis of variance test followed by the Bonferroni test, enabling multiple comparisons for all tests using GraphPad Prism10.1.0 (GraphPad Inc, USA). RESULTS: The outcomes of the biomechanical tests indicated that no statistically significant differences were found in terms of the maximum displacement (p = 0.496, 0.079) and the slope of load displacement curves (p = 0.374, 0.349) under 2 load modes between the external and internal fixation groups. The animal experiment data showed that there were minor displacements of feature points between the external and internal fixation groups without statistic difference, while the arch bar group demonstrated inferior stability. The CT analysis revealed that the best fracture healing happened in the internal fixation group, followed by the external fixation and arch baring at 28 days after fixation. The external fixation group had the shortest fixation duration (25.67 ± 3.79) min compared to internal fixation ((70.67 ± 4.51) min, p < 0.001) and arch baring ((42.00 ± 3.00) min, p = 0.046). CONCLUSION: The conclusion of this study highlighted the efficacy and reliability of this novel external fixator in managing mandibular fractures rapidly, offering a viable option for the initial stabilization of comminuted mandibular fractures in the setting of emergency rescue.

[Intelligent material classification of traditional Chinese medicine based on semantic analysis].

A method for material classification of traditional Chinese medicines based on the physical properties of powder has been established by our research group. This method involves pre-treatment of traditional Chinese medicine decoction pieces, powder preparation, and determination of physical properties, being cumbersome. In this study, the word segmentation logic of semantic analysis was adopted to establish the thesaurus and local standardized semantic word segmentation database with the macroscopic and microscopic characteristics of 36 model traditional Chinese medicines as the basic data. The physical properties of these medicines have been determined and the classification of these medicines is clear in the cluster analysis. A total of 55 keywords for powdery, fibrous, sugary, oily, and brittle materials were screened by association rules and the set inclusion and exclusion criteria, and the weights of the keywords were calculated. Furthermore, the algorithms of the keyword matching scores and the computation rules of the single or multiple material classification were established for building the intelligent model of semantic analysis for the material classification. The semantic classification results of the other 35 TCMs except Pseudostellariae Radix(multi-material medicine) agreed with the clustering results based on the physical properties of the powder, with an agreement rate of 97.22%. In model validation, the prediction results of semantic classification of traditional Chinese medicines were consistent with the clustering results based on the physical properties of powder, with an agreement rate of 83.33%. The results showed that the method of material classification based on semantic analysis was feasible, which laid a foundation for the development of intelligent decision-making technology for personalized traditional Chinese medicine preparations.

UHRF1 regulates alternative splicing by interacting with splicing factors and U snRNAs in a H3R2me involved manner.

The well-established functions of UHRF1 converge to DNA biological processes, as exemplified by DNA methylation maintenance and DNA damage repair during cell cycles. However, the potential effect of UHRF1 on RNA metabolism is largely unexplored. Here, we revealed that UHRF1 serves as a novel alternative RNA splicing regulator. The protein interactome of UHRF1 identified various splicing factors. Among them, SF3B3 could interact with UHRF1 directly and participate in UHRF1-regulated alternative splicing events. Furthermore, we interrogated the RNA interactome of UHRF1, and surprisingly, we identified U snRNAs, the canonical spliceosome components, in the purified UHRF1 complex. Unexpectedly, we found H3R2 methylation status determines the binding preference of U snRNAs, especially U2 snRNAs. The involvement of U snRNAs in UHRF1-containing complex and their binding preference to specific chromatin configuration imply a finely orchestrated mechanism at play. Our results provided the resources and pinpointed the molecular basis of UHRF1-mediated alternative RNA splicing, which will help us better our understanding of the physiological and pathological roles of UHRF1 in disease development.

Genomic evolution and the impact of SLIT2 mutation in relapsed intrahepatic cholangiocarcinoma.

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (ICC) is aggressive and has high rates of relapse, conferring poor long-term survival after curative resection. Little is known about the genomic evolution that occurs during ICC relapse. APPROACH AND RESULTS: We conducted whole-exome sequencing of 30 paired primary and relapsed tumors from 10 patients with ICC who received curative resection. We sought to identify frequently altered genes, infer tumor subclonal architectures, and track genomic evolution from primary to relapsed tumors. We examined functional effects and the mechanism of action of SLIT2, a gene specifically mutated in relapsed tumors, on tumor growth and metastasis and the tumor microenvironment. Our results indicated that relapsed ICCs were genetically derived from intrahepatic dissemination of primary tumors. However, they acquired additional mutations while maintaining most drivers, such as TP53 and IDH1. Multiregion sequencing suggested polyclonal seeding of ICC dissemination. Four of 10 relapsed ICCs acquired SLIT2 mutations that were not present in the corresponding primary tumors. Validation in an expanded sample revealed SLIT2 mutations in 2.3% (1/44) of primary ICCs and 29.5% (13/44) of relapsed ICCs. Biofunctional investigations revealed that inactivating mutation of SLIT2 resulted in activation of PI3K-Akt signaling in ICC cells, directly enhanced neutrophil chemotaxis, mediated tumor-associated neutrophil infiltration, and contributed to ICC growth and metastasis. CONCLUSIONS: We characterized genomic evolution during ICC relapse and identified SLIT2 as a driver of tumor dissemination and tumor-associated neutrophil infiltration.